Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, United States of America.
Department of Mechatronics Engineering, Incheon National University, Incheon, Republic of Korea.
PLoS One. 2020 Jan 27;15(1):e0227598. doi: 10.1371/journal.pone.0227598. eCollection 2020.
Comparative network analysis provides effective computational means for gaining novel insights into the structural and functional compositions of biological networks. In recent years, various methods have been developed for biological network alignment, whose main goal is to identify important similarities and critical differences between networks in terms of their topology and composition. A major impediment to advancing network alignment techniques has been the lack of gold-standard benchmarks that can be used for accurate and comprehensive performance assessment of such algorithms. The original NAPAbench (network alignment performance assessment benchmark) was developed to address this problem, and it has been widely utilized by many researchers for the development, evaluation, and comparison of novel network alignment techniques. In this work, we introduce NAPAbench 2-a major update of the original NAPAbench that was introduced in 2012. NAPAbench 2 includes a completely redesigned network synthesis algorithm that can generate protein-protein interaction (PPI) network families whose characteristics closely match those of the latest real PPI networks. Furthermore, the network synthesis algorithm comes with an intuitive GUI that allows users to easily generate PPI network families with an arbitrary number of networks of any size, according to a flexible user-defined phylogeny. In addition, NAPAbench 2 provides updated benchmark datasets-created using the redesigned network synthesis algorithm-which can be used for comprehensive performance assessment of network alignment algorithms and their scalability.
比较网络分析为深入了解生物网络的结构和功能组成提供了有效的计算手段。近年来，已经开发出了各种生物网络比对方法，其主要目标是根据拓扑结构和组成来识别网络之间的重要相似性和关键差异。推进网络比对技术的主要障碍是缺乏可用于准确全面评估此类算法性能的黄金标准基准。原始的 NAPAbench（网络比对性能评估基准）就是为了解决这个问题而开发的，许多研究人员都广泛使用它来开发、评估和比较新的网络比对技术。在这项工作中，我们引入了 NAPAbench 2——这是 2012 年引入的原始 NAPAbench 的重大更新。NAPAbench 2 包括一个完全重新设计的网络综合算法，可以生成与最新真实蛋白质-蛋白质相互作用（PPI）网络特征非常匹配的蛋白质-蛋白质相互作用网络家族。此外，网络综合算法带有直观的图形用户界面，允许用户根据灵活的用户定义的系统发育轻松生成具有任意数量任意大小的 PPI 网络家族。此外，NAPAbench 2 提供了更新的基准数据集——使用重新设计的网络综合算法创建——可用于全面评估网络比对算法及其可扩展性。
